Family-based association analysis with ordered categorical phenotypes, covariates and interactions

Genetic association analyses of family-based studies with ordered categorical phenotypes are often conducted using methods either for quantitative or for binary traits, which can lead to suboptimal analyses. Here we present an alternative likelihood-based method of analysis for single nucleotide polymorphism (SNP) genotypes and ordered categorical phenotypes in nuclear families of any size. Our approach, which extends our previous work for binary phenotypes, permits straightforward inclusion of covariate, gene-gene and gene-covariate interaction terms in the likelihood, incorporates a simple model for ascertainment and allows for family-specific effects in the hypothesis test. Additionally, our method produces interpretable parameter estimates and valid confidence intervals. We assess the proposed method using simulated data, and apply it to a polymorphism in the c-reactive protein (CRP) gene typed in families collected to investigate human systemic lupus erythematosus. By including sex interactions in the analysis, we show that the polymorphism is associated with anti-nuclear autoantibody (ANA) production in females, while there appears to be no effect in males.

Determinants of fruit and vegetable intake in England: a re-examination based on quantile regression

Objective To examine die sociodemographic determinants of fruit and vegetable (F&V) consumption in England and determine the differential effects of socioeconomic variables at various parts of the intake distribution, with a special focus on severely inadequate intakes Design Quantile regression, expressing F&V intake as a function of sociodemographic variables, is employed. Here, quantile regression flexibly allows variables such as ethnicity to exert effects on F&V intake that. vary depending oil existing levels of intake. Setting The 2003 Health survey of England. Subjects Data were from 11044 adult individuals. Results The influence of particular sociodemographic variables is found to vary significantly across the intake distribution We conclude that women consume more F&V than men, Asians and Hacks mole dian Whites, co-habiting individuals more than single-living ones Increased incomes and education also boost intake However, the key general finding of the present study is that the influence of most variables is relatively weak in the area of greatest concern, i e among those with the most inadequate intakes in any reference group. Conclusions. Our findings emphasise the importance of allowing the effects of socio-economic drivers to vary across the intake distribution The main finding, that variables which exert significant influence on F&V Intake at other parts Of the conditional distribution have a relatively weak influence at the lower tail, is cause for concern. It implies that in any defined group, those consuming the lease F&V are hard to influence using compaigns or policy levers.

Statistical methods for ordered categorical data based on a constrained odds model

The proportional odds model provides a powerful tool for analysing ordered categorical data and setting sample size, although for many clinical trials its validity is questionable. The purpose of this paper is to present a new class of constrained odds models which includes the proportional odds model. The efficient score and Fisher's information are derived from the profile likelihood for the constrained odds model. These results are new even for the special case of proportional odds where the resulting statistics define the Mann-Whitney test. A strategy is described involving selecting one of these models in advance, requiring assumptions as strong as those underlying proportional odds, but allowing a choice of such models. The accuracy of the new procedure and its power are evaluated.

Variance estimation for systematic sampling from deliberately ordered populations

The systematic sampling (SYS) design (Madow and Madow, 1944) is widely used by statistical offices due to its simplicity and efficiency (e.g., Iachan, 1982). But it suffers from a serious defect, namely, that it is impossible to unbiasedly estimate the sampling variance (Iachan, 1982) and usual variance estimators (Yates and Grundy, 1953) are inadequate and can overestimate the variance significantly (Särndal et al., 1992). We propose a novel variance estimator which is less biased and that can be implemented with any given population order. We will justify this estimator theoretically and with a Monte Carlo simulation study.

Low-temperature synthesis of ordered graphite nanofibres using nickel(II)-exchanged zeolites

Ordered graphite nanofibre formation has been observed at exceptionally low temperatures on admission of ethyne to zeolite Y, which had been exchanged with Ni(II). The samples have been characterised by TEM, carbon analysis, and electronic spectroscopy. Formation of the nanofibres requires no hydrogen, and was not observed when cation exchange was carried out at acidic pH. The observed fibres resemble herring-bone nanofibrils, growing from nickel particles, and ca. 90% have diameters in the range 35-40 nm. Similar fibres have also been grown using nickel-exchanged zeolite beta.

Peroxides in ordered nanoporous silicas: clean alternatives to transition metal oxidants for the removal of toxic gases

Ordered nano-structured MCM-48 silica containing sodium peroxydisulfate is a novel, highly effective material for the decomposition of HCN under ambient conditions.

Low-temperature sol-gel preparation of ordered nanoparticles of tungsten carbide/oxide

Tungsten carbide/oxide particles have been prepared by the gel precipitation of tungstic acid in the presence of an organic gelling agent [10% ammonium poly(acrylic acid) in water, supplied by Ciba Specialty Chemicals]. The feed solution; a homogeneous mixture of sodium tungstate and ammonium poly(acrylic acid) in water, was dropped from a 1-mm jet into hydrochloric acid saturated hexanol/concentrated hydrochloric acid to give particles of a mixture of tungstic acid and poly(acrylic acid), which, after drying in air at 100 degrees C and heating to 900 degrees C in argon for 2 h, followed by heating in carbon dioxide for a further 2 h and cooling, gives a mixture of WO, WC, and a trace of NaxWO3, with the carbon for the formation of WC being provided by the thermal carbonization of poly(acrylic acid). The pyrolyzed product is friable and easily broken down in a pestle and mortar to a fine powder or by ultrasonics, in water, to form a stable colloid. The temperature of carbide formation by this process is significantly lower (900 degrees C) than that reported for the commercial preparation of tungsten carbide, typically > 1400 degrees C. In addition, the need for prolonged grinding of the constituents is obviated because the reacting moieties are already in intimate contact on a molecular basis. X-ray diffraction, particle sizing, transmission electron microscopy, surface area, and pore size distribution studies have been carried out, and possible uses are suggested. A flow diagram for the process is described.

Anion directed template synthesis of Cu(II) complexes of a N,N,O donor mono-condensed Schiff base ligand: A molecular scaffold forming highly ordered H-bonded rectangular grids

Anion directed, template syntheses of two dinuclear copper(II) complexes of mono-condensed Schiff base ligand Hdipn (4-[(3-aminopentylimino)-methyl]-benzene-1,3-diol) involving 2,4- dihydroxybenzaldehyde and 1,3-diaminopentane were realized in the presence of bridging azide and acetate anions. Both complexes, [Cu-2(dipn)(2)(N-3)(2)] (1) and [Cu-2(dip(n))(2)(OAc)(2)] (2) have been characterized by X-ray crystallography. The two mononuclear units are joined together by basal-apical, double end-on azido bridges in complex 1 and by basal-apical, double mono-atomic acetate oxygen-bridges in 2. Both complexes form rectangular grid-like supramolecular structures via H-bonds connecting the azide or acetate anion and the p-hydroxy group of 2,4- dihydroxybenzaldehyde. Variable-temperature (300-2 K) magnetic susceptibility measurements reveal that complex 1 has antiferromagnetic coupling (J = -2.10 cm (1)) through the azide bridge while 2 has intra-dimer ferromagnetic coupling through the acetate bridge and inter-dimer antiferromagnetic coupling through H-bonds (J = 2.85 cm (1), J' = -1.08 cm (1)). (C) 2009 Elsevier B. V. All rights reserved.

A method of synthesis of silicious inorganic ordered materials (MCM-41-SBA-1) employing polyacrylic acid-C(n)TAB-TEOS nanoassemblies

In this work we describe the synthesis of a variety of MCM-41 type hexagonal and SBA-1 type cubic mesostructures and mesoporous silicious materials employing a novel synthesis concept based on polyacrylic acid (Pac)-C(n)TAB complexes as backbones of the developing structures. The ordered porosity of the solids was established by XRD and TEM techniques. The synthesis concept makes use of Pac-C(n)TAB nanoassemblies as a preformed scaffold, formed by the gradual increase of pH. On this starting matrix the inorganic precursor species SiO2 precipitate via hydrolysis of TEOS under the influence of increasing pH. The molecular weight (MW) of Pac, as well as the length of carbon chain in C,TAB, determine the physical and structural characteristics of the obtained materials. Longer chain surfactants (C(16)TAB) lead to the formation of hexagonal phase, while shorter chain surfactants (C(14)TAB, C(12)TAB) favor the SBA-1 phase. Lower MW of Pac (approximate to2000) leads to better-organized structures compared to higher MW ( 450,000), which leads to worm-like mesostructures. Cell parameters and pore size increase with increasing polyelectrolyte and/or surfactant chain, while at the same time SEM photography reveals that the particle size decreases. Conductivity experiments provide some insight into the proposed self-assembling pathway. (C) 2003 Elsevier Inc. All rights reserved.

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Regression, developmental trajectory and associated problems in disorders in the autism spectrum: the SNAP study

We report rates of regression and associated findings in a population derived group of 255 children aged 9-14 years, participating in a prevalence study of autism spectrum disorders (ASD); 53 with narrowly defined autism, 105 with broader ASD and 97 with non-ASD neurodevelopmental problems, drawn from those with special educational needs within a population of 56,946 children. Language regression was reported in 30% with narrowly defined autism, 8% with broader ASD and less than 3% with developmental problems without ASD. A smaller group of children were identified who underwent a less clear setback. Regression was associated with higher rates of autistic symptoms and a deviation in developmental trajectory. Regression was not associated with epilepsy or gastrointestinal problems.

A sparse kernel density estimation algorithm using forward constrained regression

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The leave-one-out (LOO) test score is used for kernel selection. The jackknife parameter estimator subject to positivity constraint check is used for the parameter estimation of a single parameter at each forward step. As such the proposed approach is simple to implement and the associated computational cost is very low. An illustrative example is employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to that of the classical Parzen window estimate.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.